Adejumo Develops Advanced Retinal Image Processing Techniques for Early Detection of Diabetic Eye Diseases
Ayodeji Ake
A Biomedical Engineering Researcher at the University of Illinois Chicago, Tobiloba Adejumo, has developed imaging methods for classifying retinal blood vessels, providing a critical foundation for advancing early detection of diabetic eye disease.
In a note shared with a national daily, Adejumo emphasized that technology must meet the environments it is intended to serve.
Diabetic retinopathy is the most common eye disease caused by diabetes and a leading cause of vision impairment and blindness worldwide. Globally, millions are affected, with some regions, such as Africa, experiencing particularly high prevalence rates according to a scientific report published in Nature.
Adejumo’s work focuses on improving diagnostic tools for diabetic retinopathy, a condition that can lead to blindness if untreated. By advancing image processing techniques and integrating them with artificial intelligence approaches, he aims to enhance the accuracy and accessibility of retinal exams, enabling earlier intervention and diagnosis.
“Innovation is only meaningful when it addresses the practical realities of clinical practice worldwide,” he said, highlighting the importance of creating tools that can be used effectively in real-world healthcare settings.
Adejumo’s academic journey began in computer science, which provided him with a strong technical foundation. This experience, combined with his leadership in educational technology programmes, eventually led him to focus on biomedical engineering.
His pivotal career moment came when he recognized the potential of spectral-domain Optical Coherence Tomography, a non-invasive imaging modality that captures high-resolution images of the retina.
The researcher said his work contributed to a significant advancement in the field with a novel artery-vein classification method for OCT images, which was published in ‘Biomedical Optics Express’ in 2022.
The paper became one of the journal’s most downloaded and viewed articles in its category. Across all his scientific publications, Adejumo’s research has been cited more than 200 times, according to Google Scholar.
A major milestone in his career occurred in 2024 when his work was cited in a peer-reviewed article by researchers at the University of Alabama at Birmingham, in collaboration with NASA scientists.
The paper, published in MDPI Life, highlighted how Adejumo’s methods for analyzing OCT profiles enable reliable AV classification and support AI-based diagnostic advancements.
Adejumo has also presented his findings at leading international conferences. At the 2024 SPIE Photonics West Conference, he presented “Adaptive vessel tracing and segmentation in OCT enables robust quantification of blood vessel wall-to-lumen ratio in the retina,” research that advances the understanding of vascular changes associated with neurodegenerative diseases such as Alzheimer’s. This work was published in the SPIE Proceedings, Ophthalmic Technologies XXXIV, in 2024.
In addition to his research, Adejumo is completing his doctoral studies at the University of Illinois, Chicago, with degree conferral expected in May 2025. He emphasised the focus on advancing diagnostic technologies that are both high-performance and broadly accessible.
His work represents a significant step forward in the effort to combat vision loss caused by diabetes, offering the potential for earlier detection and more effective treatments.
